A temporal prediction filter is used in a video compression process to predict a target image from a set of previously decoded reference images. The temporal prediction process is effective at removing a significant amount of temporal redundancy, which generally results in a higher coding efficiency. The prediction process uses a set of motion vectors and a filter that operates on the motion vectors to predict the target image.
For example, the prediction method divides a reference image 110 into multiple fixed-size blocks 120, as shown in FIG. 1. Each block has an associated motion vector to describe the motion of the block relative to the target image. The motion vectors are shown by the white dots in image 110. A temporal prediction filter uses the associated motion vector to perform a simple motion compensation technique on each block in the reference image to predict the location of the block in the target image. Thus, each block in the target image is estimated from a block in the reference image using the single motion vector. However, this approach treats each motion vector independently and is not adaptive to image features.
Conventional temporal filters, which use a single motion vector to predict the location of an associated block, or rely on a filter defined for a regular motion vector pattern, need a regular distribution of motion vectors to perform temporal prediction. Therefore, they are unable to adapt the prediction process to an irregular pattern of motion vectors. There is a need for a filter that can locally adapt its tap and filter coefficients to the variations of an irregular pattern of motion vectors, and also has the flexibility to adapt to object boundaries and spatial textures. There is also a need for a efficient and effective motion estimation procedure that can use the temporal filter to estimate each motion vector value by taking into account the effects of neighboring motion vectors.